We ship ai software development projects in Dubai for teams that need working software this quarter, not a strategy deck for next.
For Dubai companies, we treat ai software development as engineering — versioned, tested, monitored — not as a science project you renew every year. Most briefs we see out of Dubai come from financial services, real estate, and logistics — the vertical shifts, but the shape of the problem does not. In practice this looks like AI-enabled software products built the same way regular software is — with tests, review, deploys, and monitoring — the code we ship is boring by design and easy for the next engineer to read. We handle infrastructure, evaluation, and handover so your team owns the system after we leave, not a black box only we understand. Our team ships from Dubai and delivers into Dubai and the wider GCC, so timezone, language, and data-residency get handled up front. We keep ai software development teams small on purpose — usually three to five people on your project — so the person building understands the full system, not just their slice. If you're comparing agencies, ask us how we measure success before we quote — that's usually the fastest way to see who's serious.
The Gulf's busiest commercial hub is competitive, and Dubai operators don't get credit for AI theatre. What ships and reduces cost — or lifts revenue — is what earns the next budget round, and that's what we optimise for.
AI features live inside a normal codebase with normal tests, code review, PR discipline, and CI/CD. They ship the same way any other feature ships. No AI island.
Every AI feature has a p95 latency budget and a cost-per-request target. Product decisions are made with those numbers on the table.
AI features ship behind feature flags, get tested on a fraction of traffic first, and roll out cleanly. When something misbehaves, it's turned off in seconds.
You get a codebase your engineers can read, the AI-specific parts documented, and a runbook for the common failure modes. No black boxes.
Products where AI is central to the value — from a first working release through public launch, with the software discipline that keeps them alive after.
Add AI features (drafting, summarising, personalising, extracting) to a product you already ship, without destabilising the codebase around them.
Internal tools where AI is a first-class citizen — replacing spreadsheets, playbooks, and slow processes with software people actually want to use.
For SaaS operators in DIFC, DMCC, and the tech free zones, we ship AI-enabled software that plugs into the product you already sell, not a demo bolted on top. Auth, billing, and multi-tenant data separation are treated as day-one requirements, not backlog items.
It means building software where AI is a first-class feature, using the engineering practices that keep normal software alive: version control, code review, tests, staged deploys, feature flags, monitoring. Most 'AI projects' fail because they skip these — the AI part is treated as special. It isn't. It just has one extra dimension (model behaviour) that needs its own evals and monitoring.
AI development is the general umbrella. AI software development specifically means: the deliverable is a shipped software product with AI features, not a model or a Jupyter notebook. That framing matters because it changes what you build — you spend a lot of time on the software around the AI, not just on the AI itself.
Per-feature cost budgets, cheaper models for cheaper work, caching and prompt-level optimisation, and streaming so users don't pay for completions they don't wait for. Every AI feature has a dashboard showing cost per week and cost per active user, so when usage scales the finance conversation has real numbers, not surprises.
A first working release with one AI feature inside an existing product is usually four to six weeks. New AI-native products from zero to public launch typically run three to six months, depending on how much surrounding software (auth, billing, admin, integrations) has to be built alongside the AI. We ship weekly through both.
Yes. We prefer to work inside your codebase, following your conventions, using your CI/CD, going through your code review. That way what we build is legible to your team from day one and doesn't require a hand-over ceremony to maintain. If you don't have a codebase yet, we set one up in the shape we'd want to hand over — Next.js, TypeScript, Postgres, standard cloud, boring by design.
Yes. Most projects include the infra as part of the delivery — Terraform for the cloud setup, CI/CD for deploys, monitoring and error tracking wired in, and a runbook for the common failure modes. Handover includes access, secrets rotation, and a walkthrough so your team can operate the system from day one after we leave.
Yes — most of our client base sits in DIFC, DMCC, JAFZA, and Dubai Internet City. Vendor onboarding and procurement look different in each free zone, and we've been through them enough times to move faster than a firm doing it for the first time. Contracts, POs, and invoicing route through a UAE mainland entity we already run.
SM Stratagem builds mlops services in Dubai, United Arab Emirates. ML delivery, repeatable. Training pipelines you own. Monitoring and drift built in.
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We'll scope the first release, define the eval set, and give you a build plan you can hand to any engineering team — ours or yours.